Merge pull request #43 from zonghaoyuan/worktree-ai-sdk-migration
refactor(ai-client): unify OpenAI-compatible path to AI SDK generateText
This commit is contained in:
@@ -55,7 +55,6 @@ export async function POST(req: Request) {
|
|||||||
config.vision,
|
config.vision,
|
||||||
body.imageDataUrl,
|
body.imageDataUrl,
|
||||||
STYLE_EXTRACTION_PROMPT,
|
STYLE_EXTRACTION_PROMPT,
|
||||||
{ responseFormat: "json_object" },
|
|
||||||
);
|
);
|
||||||
|
|
||||||
let parsed: { stylePrompt?: string };
|
let parsed: { stylePrompt?: string };
|
||||||
|
|||||||
+5
-142
@@ -1,69 +1,15 @@
|
|||||||
import { generateText } from "ai";
|
import { generateText } from "ai";
|
||||||
import type { LanguageModelUsage, ModelMessage } from "ai";
|
import type { LanguageModelUsage, ModelMessage } from "ai";
|
||||||
import { createAnthropic } from "@ai-sdk/anthropic";
|
import type { ProviderConfig } from "@infiplot/types";
|
||||||
import { createGoogleGenerativeAI } from "@ai-sdk/google";
|
import { createLanguageModel, resolveProtocol } from "./model";
|
||||||
import type { ProviderConfig, ProviderProtocol } from "@infiplot/types";
|
|
||||||
import { fetchWithRetry } from "./fetchWithRetry";
|
|
||||||
import { normalizeBaseUrl } from "./normalizeUrl";
|
|
||||||
|
|
||||||
export type ChatMessage = {
|
export type ChatMessage = {
|
||||||
role: "system" | "user" | "assistant";
|
role: "system" | "user" | "assistant";
|
||||||
content: string;
|
content: string;
|
||||||
};
|
};
|
||||||
|
|
||||||
// Different providers expose prompt-cache stats under different keys. We probe
|
|
||||||
// for the three forms we've seen in the wild and fall back to total tokens
|
|
||||||
// when no cache field exists.
|
|
||||||
//
|
|
||||||
// DeepSeek (v3+) usage.prompt_cache_hit_tokens / prompt_cache_miss_tokens
|
|
||||||
// OpenAI / o-series usage.prompt_tokens_details.cached_tokens
|
|
||||||
// Anthropic / others usage.cache_read_input_tokens / cache_creation_input_tokens
|
|
||||||
// No-cache (MiMo,
|
|
||||||
// local Ollama, …) only prompt_tokens / completion_tokens — print those
|
|
||||||
// so we still get a rough cost baseline.
|
|
||||||
type Usage = {
|
|
||||||
prompt_tokens?: number;
|
|
||||||
completion_tokens?: number;
|
|
||||||
prompt_cache_hit_tokens?: number;
|
|
||||||
prompt_cache_miss_tokens?: number;
|
|
||||||
prompt_tokens_details?: { cached_tokens?: number };
|
|
||||||
cache_read_input_tokens?: number;
|
|
||||||
cache_creation_input_tokens?: number;
|
|
||||||
};
|
|
||||||
|
|
||||||
function summarizeUsage(tag: string, usage: Usage | undefined): string {
|
|
||||||
if (!usage) return `[cache] ${tag} no-usage`;
|
|
||||||
const prompt = usage.prompt_tokens ?? 0;
|
|
||||||
const completion = usage.completion_tokens ?? 0;
|
|
||||||
// DeepSeek-style
|
|
||||||
if (typeof usage.prompt_cache_hit_tokens === "number") {
|
|
||||||
const hit = usage.prompt_cache_hit_tokens;
|
|
||||||
const miss = usage.prompt_cache_miss_tokens ?? Math.max(0, prompt - hit);
|
|
||||||
const denom = hit + miss;
|
|
||||||
const rate = denom > 0 ? ((hit / denom) * 100).toFixed(1) : "n/a";
|
|
||||||
return `[cache] ${tag} hit=${hit} miss=${miss} rate=${rate}% completion=${completion}`;
|
|
||||||
}
|
|
||||||
// OpenAI-style
|
|
||||||
const oaiCached = usage.prompt_tokens_details?.cached_tokens;
|
|
||||||
if (typeof oaiCached === "number") {
|
|
||||||
const miss = Math.max(0, prompt - oaiCached);
|
|
||||||
const rate = prompt > 0 ? ((oaiCached / prompt) * 100).toFixed(1) : "n/a";
|
|
||||||
return `[cache] ${tag} hit=${oaiCached} miss=${miss} rate=${rate}% completion=${completion}`;
|
|
||||||
}
|
|
||||||
// Anthropic-style
|
|
||||||
if (typeof usage.cache_read_input_tokens === "number") {
|
|
||||||
const hit = usage.cache_read_input_tokens;
|
|
||||||
const create = usage.cache_creation_input_tokens ?? 0;
|
|
||||||
const denom = hit + create + prompt;
|
|
||||||
const rate = denom > 0 ? ((hit / denom) * 100).toFixed(1) : "n/a";
|
|
||||||
return `[cache] ${tag} hit=${hit} create=${create} miss=${prompt} rate=${rate}% completion=${completion}`;
|
|
||||||
}
|
|
||||||
// No cache field at all
|
|
||||||
return `[cache] ${tag} prompt=${prompt} completion=${completion} (provider didn't report cache stats)`;
|
|
||||||
}
|
|
||||||
|
|
||||||
// AI SDK 6 unifies cache stats across providers into usage.inputTokenDetails,
|
// AI SDK 6 unifies cache stats across providers into usage.inputTokenDetails,
|
||||||
// so a single shape covers Anthropic + Gemini (no per-provider probing).
|
// so a single shape covers Anthropic, Gemini, and OpenAI-compatible providers.
|
||||||
function summarizeSdkUsage(
|
function summarizeSdkUsage(
|
||||||
tag: string,
|
tag: string,
|
||||||
usage: LanguageModelUsage | undefined,
|
usage: LanguageModelUsage | undefined,
|
||||||
@@ -82,43 +28,16 @@ function summarizeSdkUsage(
|
|||||||
return `[cache] ${tag} input=${input} completion=${output} (provider didn't report cache stats)`;
|
return `[cache] ${tag} input=${input} completion=${output} (provider didn't report cache stats)`;
|
||||||
}
|
}
|
||||||
|
|
||||||
// text/vision default to the OpenAI-compatible wire protocol when unset.
|
|
||||||
function resolveTextProtocol(config: ProviderConfig): ProviderProtocol {
|
|
||||||
return config.provider ?? "openai_compatible";
|
|
||||||
}
|
|
||||||
|
|
||||||
export async function chat(
|
export async function chat(
|
||||||
config: ProviderConfig,
|
config: ProviderConfig,
|
||||||
messages: ChatMessage[],
|
messages: ChatMessage[],
|
||||||
opts?: {
|
opts?: {
|
||||||
temperature?: number;
|
temperature?: number;
|
||||||
responseFormat?: "json_object" | "text";
|
|
||||||
tag?: string;
|
tag?: string;
|
||||||
},
|
},
|
||||||
): Promise<string> {
|
): Promise<string> {
|
||||||
const protocol = resolveTextProtocol(config);
|
const protocol = resolveProtocol(config);
|
||||||
if (protocol === "anthropic" || protocol === "google") {
|
const model = createLanguageModel(config, protocol);
|
||||||
return chatViaAiSdk(config, messages, opts, protocol);
|
|
||||||
}
|
|
||||||
return chatOpenAiCompatible(config, messages, opts);
|
|
||||||
}
|
|
||||||
|
|
||||||
// Native Anthropic / Gemini via the Vercel AI SDK. response_format is not sent
|
|
||||||
// (Anthropic has no JSON mode); the engine relies on parseJsonLoose downstream,
|
|
||||||
// matching how it already tolerates loose JSON from every provider.
|
|
||||||
async function chatViaAiSdk(
|
|
||||||
config: ProviderConfig,
|
|
||||||
messages: ChatMessage[],
|
|
||||||
opts: { temperature?: number; tag?: string } | undefined,
|
|
||||||
protocol: "anthropic" | "google",
|
|
||||||
): Promise<string> {
|
|
||||||
const baseURL = normalizeBaseUrl(config.baseUrl, protocol);
|
|
||||||
const model =
|
|
||||||
protocol === "anthropic"
|
|
||||||
? createAnthropic({ apiKey: config.apiKey, baseURL })(config.model)
|
|
||||||
: createGoogleGenerativeAI({ apiKey: config.apiKey, baseURL })(
|
|
||||||
config.model,
|
|
||||||
);
|
|
||||||
|
|
||||||
const system = messages.find((m) => m.role === "system")?.content;
|
const system = messages.find((m) => m.role === "system")?.content;
|
||||||
const convo: ModelMessage[] = messages
|
const convo: ModelMessage[] = messages
|
||||||
@@ -142,59 +61,3 @@ async function chatViaAiSdk(
|
|||||||
}
|
}
|
||||||
return text;
|
return text;
|
||||||
}
|
}
|
||||||
|
|
||||||
async function chatOpenAiCompatible(
|
|
||||||
config: ProviderConfig,
|
|
||||||
messages: ChatMessage[],
|
|
||||||
opts?: {
|
|
||||||
temperature?: number;
|
|
||||||
responseFormat?: "json_object" | "text";
|
|
||||||
tag?: string;
|
|
||||||
},
|
|
||||||
): Promise<string> {
|
|
||||||
const url = `${normalizeBaseUrl(config.baseUrl, "openai_compatible")}/chat/completions`;
|
|
||||||
const body: Record<string, unknown> = {
|
|
||||||
model: config.model,
|
|
||||||
messages,
|
|
||||||
temperature: opts?.temperature ?? 0.9,
|
|
||||||
};
|
|
||||||
if (opts?.responseFormat === "json_object") {
|
|
||||||
body.response_format = { type: "json_object" };
|
|
||||||
}
|
|
||||||
|
|
||||||
const res = await fetchWithRetry(url, {
|
|
||||||
method: "POST",
|
|
||||||
headers: {
|
|
||||||
"Content-Type": "application/json",
|
|
||||||
Authorization: `Bearer ${config.apiKey}`,
|
|
||||||
},
|
|
||||||
body: JSON.stringify(body),
|
|
||||||
});
|
|
||||||
|
|
||||||
const text = await res.text();
|
|
||||||
if (!res.ok) {
|
|
||||||
throw new Error(`Chat API error ${res.status}: ${text}`);
|
|
||||||
}
|
|
||||||
|
|
||||||
let json: {
|
|
||||||
choices: { message: { content: string } }[];
|
|
||||||
usage?: Usage;
|
|
||||||
};
|
|
||||||
try {
|
|
||||||
json = JSON.parse(text);
|
|
||||||
} catch {
|
|
||||||
throw new Error(`Chat API returned invalid JSON: ${text.slice(0, 500)}`);
|
|
||||||
}
|
|
||||||
|
|
||||||
// Guard against empty choices array or missing message/content fields
|
|
||||||
const content = json.choices?.[0]?.message?.content;
|
|
||||||
if (typeof content !== "string") {
|
|
||||||
throw new Error(
|
|
||||||
`Chat API returned no content. Response: ${text.slice(0, 500)}`
|
|
||||||
);
|
|
||||||
}
|
|
||||||
|
|
||||||
console.log(summarizeUsage(opts?.tag ?? "chat", json.usage));
|
|
||||||
|
|
||||||
return content;
|
|
||||||
}
|
|
||||||
|
|||||||
@@ -0,0 +1,23 @@
|
|||||||
|
import { createAnthropic } from "@ai-sdk/anthropic";
|
||||||
|
import { createGoogleGenerativeAI } from "@ai-sdk/google";
|
||||||
|
import { createOpenAI } from "@ai-sdk/openai";
|
||||||
|
import type { ProviderConfig, ProviderProtocol } from "@infiplot/types";
|
||||||
|
import { normalizeBaseUrl } from "./normalizeUrl";
|
||||||
|
|
||||||
|
export function resolveProtocol(config: ProviderConfig): ProviderProtocol {
|
||||||
|
return config.provider ?? "openai_compatible";
|
||||||
|
}
|
||||||
|
|
||||||
|
export function createLanguageModel(config: ProviderConfig, protocol: ProviderProtocol) {
|
||||||
|
const baseURL = normalizeBaseUrl(config.baseUrl, protocol);
|
||||||
|
switch (protocol) {
|
||||||
|
case "anthropic":
|
||||||
|
return createAnthropic({ apiKey: config.apiKey, baseURL })(config.model);
|
||||||
|
case "google":
|
||||||
|
return createGoogleGenerativeAI({ apiKey: config.apiKey, baseURL })(config.model);
|
||||||
|
case "openai_compatible":
|
||||||
|
case "openai":
|
||||||
|
default:
|
||||||
|
return createOpenAI({ apiKey: config.apiKey, baseURL }).chat(config.model);
|
||||||
|
}
|
||||||
|
}
|
||||||
+5
-109
@@ -1,10 +1,7 @@
|
|||||||
import { generateText } from "ai";
|
import { generateText } from "ai";
|
||||||
import type { ModelMessage } from "ai";
|
import type { ModelMessage } from "ai";
|
||||||
import { createAnthropic } from "@ai-sdk/anthropic";
|
import type { ProviderConfig } from "@infiplot/types";
|
||||||
import { createGoogleGenerativeAI } from "@ai-sdk/google";
|
import { createLanguageModel, resolveProtocol } from "./model";
|
||||||
import type { ProviderConfig, ProviderProtocol } from "@infiplot/types";
|
|
||||||
import { fetchWithRetry } from "./fetchWithRetry";
|
|
||||||
import { normalizeBaseUrl } from "./normalizeUrl";
|
|
||||||
|
|
||||||
const VISION_TIMEOUT_MS = 60_000;
|
const VISION_TIMEOUT_MS = 60_000;
|
||||||
|
|
||||||
@@ -13,55 +10,20 @@ export async function interpretClick(
|
|||||||
imageBase64: string,
|
imageBase64: string,
|
||||||
prompt: string,
|
prompt: string,
|
||||||
): Promise<string> {
|
): Promise<string> {
|
||||||
// Wrap the raw base64 in a PNG data URL — the Canvas annotator on the
|
|
||||||
// client encodes as PNG. analyzeImageDataUrl handles the actual request.
|
|
||||||
return analyzeImageDataUrl(
|
return analyzeImageDataUrl(
|
||||||
config,
|
config,
|
||||||
`data:image/png;base64,${imageBase64}`,
|
`data:image/png;base64,${imageBase64}`,
|
||||||
prompt,
|
prompt,
|
||||||
{ responseFormat: "json_object" },
|
|
||||||
);
|
);
|
||||||
}
|
}
|
||||||
|
|
||||||
// text/vision default to the OpenAI-compatible wire protocol when unset.
|
|
||||||
function resolveVisionProtocol(config: ProviderConfig): ProviderProtocol {
|
|
||||||
return config.provider ?? "openai_compatible";
|
|
||||||
}
|
|
||||||
|
|
||||||
/**
|
|
||||||
* General single-image vision call. Accepts a complete data URL (preserves
|
|
||||||
* the source mime type, e.g. webp/jpeg) and lets the caller opt out of
|
|
||||||
* `response_format: json_object` for free-form text responses.
|
|
||||||
*/
|
|
||||||
export async function analyzeImageDataUrl(
|
export async function analyzeImageDataUrl(
|
||||||
config: ProviderConfig,
|
config: ProviderConfig,
|
||||||
imageDataUrl: string,
|
imageDataUrl: string,
|
||||||
prompt: string,
|
prompt: string,
|
||||||
opts: { responseFormat?: "json_object" | "text" } = {},
|
|
||||||
): Promise<string> {
|
): Promise<string> {
|
||||||
const protocol = resolveVisionProtocol(config);
|
const protocol = resolveProtocol(config);
|
||||||
if (protocol === "anthropic" || protocol === "google") {
|
const model = createLanguageModel(config, protocol);
|
||||||
return analyzeViaAiSdk(config, imageDataUrl, prompt, protocol);
|
|
||||||
}
|
|
||||||
return analyzeOpenAiCompatible(config, imageDataUrl, prompt, opts);
|
|
||||||
}
|
|
||||||
|
|
||||||
// Native Anthropic / Gemini multimodal via the AI SDK. The image part takes
|
|
||||||
// the full data URL directly; the SDK decodes it. response_format is not sent
|
|
||||||
// (no JSON mode on Anthropic) — the engine's parseJsonLoose handles output.
|
|
||||||
async function analyzeViaAiSdk(
|
|
||||||
config: ProviderConfig,
|
|
||||||
imageDataUrl: string,
|
|
||||||
prompt: string,
|
|
||||||
protocol: "anthropic" | "google",
|
|
||||||
): Promise<string> {
|
|
||||||
const baseURL = normalizeBaseUrl(config.baseUrl, protocol);
|
|
||||||
const model =
|
|
||||||
protocol === "anthropic"
|
|
||||||
? createAnthropic({ apiKey: config.apiKey, baseURL })(config.model)
|
|
||||||
: createGoogleGenerativeAI({ apiKey: config.apiKey, baseURL })(
|
|
||||||
config.model,
|
|
||||||
);
|
|
||||||
|
|
||||||
const messages: ModelMessage[] = [
|
const messages: ModelMessage[] = [
|
||||||
{
|
{
|
||||||
@@ -80,6 +42,7 @@ async function analyzeViaAiSdk(
|
|||||||
model,
|
model,
|
||||||
messages,
|
messages,
|
||||||
temperature: 0.2,
|
temperature: 0.2,
|
||||||
|
maxRetries: 0,
|
||||||
abortSignal: timeoutCtrl.signal,
|
abortSignal: timeoutCtrl.signal,
|
||||||
});
|
});
|
||||||
if (typeof text !== "string" || text.length === 0) {
|
if (typeof text !== "string" || text.length === 0) {
|
||||||
@@ -90,70 +53,3 @@ async function analyzeViaAiSdk(
|
|||||||
clearTimeout(timeoutId);
|
clearTimeout(timeoutId);
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
async function analyzeOpenAiCompatible(
|
|
||||||
config: ProviderConfig,
|
|
||||||
imageDataUrl: string,
|
|
||||||
prompt: string,
|
|
||||||
opts: { responseFormat?: "json_object" | "text" } = {},
|
|
||||||
): Promise<string> {
|
|
||||||
const url = `${normalizeBaseUrl(config.baseUrl, "openai_compatible")}/chat/completions`;
|
|
||||||
|
|
||||||
const body: Record<string, unknown> = {
|
|
||||||
model: config.model,
|
|
||||||
messages: [
|
|
||||||
{
|
|
||||||
role: "user",
|
|
||||||
content: [
|
|
||||||
{ type: "text", text: prompt },
|
|
||||||
{ type: "image_url", image_url: { url: imageDataUrl } },
|
|
||||||
],
|
|
||||||
},
|
|
||||||
],
|
|
||||||
temperature: 0.2,
|
|
||||||
};
|
|
||||||
if (opts.responseFormat === "json_object") {
|
|
||||||
body.response_format = { type: "json_object" };
|
|
||||||
}
|
|
||||||
|
|
||||||
const timeoutCtrl = new AbortController();
|
|
||||||
const timeoutId = setTimeout(() => timeoutCtrl.abort(), VISION_TIMEOUT_MS);
|
|
||||||
|
|
||||||
let res: Response;
|
|
||||||
try {
|
|
||||||
res = await fetchWithRetry(url, {
|
|
||||||
method: "POST",
|
|
||||||
headers: {
|
|
||||||
"Content-Type": "application/json",
|
|
||||||
Authorization: `Bearer ${config.apiKey}`,
|
|
||||||
},
|
|
||||||
body: JSON.stringify(body),
|
|
||||||
signal: timeoutCtrl.signal,
|
|
||||||
retries: 0,
|
|
||||||
});
|
|
||||||
} finally {
|
|
||||||
clearTimeout(timeoutId);
|
|
||||||
}
|
|
||||||
|
|
||||||
const text = await res.text();
|
|
||||||
if (!res.ok) {
|
|
||||||
throw new Error(`Vision API error ${res.status}: ${text}`);
|
|
||||||
}
|
|
||||||
|
|
||||||
let json: { choices: { message: { content: string } }[] };
|
|
||||||
try {
|
|
||||||
json = JSON.parse(text);
|
|
||||||
} catch {
|
|
||||||
throw new Error(`Vision API returned invalid JSON: ${text.slice(0, 500)}`);
|
|
||||||
}
|
|
||||||
|
|
||||||
// Guard against empty choices array or missing message/content fields
|
|
||||||
const content = json.choices?.[0]?.message?.content;
|
|
||||||
if (typeof content !== "string") {
|
|
||||||
throw new Error(
|
|
||||||
`Vision API returned no content. Response: ${text.slice(0, 500)}`
|
|
||||||
);
|
|
||||||
}
|
|
||||||
|
|
||||||
return content;
|
|
||||||
}
|
|
||||||
|
|||||||
@@ -53,7 +53,7 @@ export async function runArchitect(
|
|||||||
{ role: "system", content: ARCHITECT_SYSTEM },
|
{ role: "system", content: ARCHITECT_SYSTEM },
|
||||||
{ role: "user", content: buildArchitectUserMessage(session) },
|
{ role: "user", content: buildArchitectUserMessage(session) },
|
||||||
],
|
],
|
||||||
{ temperature: 0.85, responseFormat: "json_object", tag: "architect" },
|
{ temperature: 0.85, tag: "architect" },
|
||||||
);
|
);
|
||||||
|
|
||||||
const parsed = parseJsonLoose<RawStoryState>(raw);
|
const parsed = parseJsonLoose<RawStoryState>(raw);
|
||||||
|
|||||||
@@ -56,7 +56,7 @@ async function runDesignLLM(
|
|||||||
content: buildCharacterDesignerUserMessage(charName, session),
|
content: buildCharacterDesignerUserMessage(charName, session),
|
||||||
},
|
},
|
||||||
],
|
],
|
||||||
{ temperature: 0.7, responseFormat: "json_object", tag: "character-designer" },
|
{ temperature: 0.7, tag: "character-designer" },
|
||||||
);
|
);
|
||||||
return parseJsonLoose<CharacterDesignOutput>(raw);
|
return parseJsonLoose<CharacterDesignOutput>(raw);
|
||||||
}
|
}
|
||||||
|
|||||||
@@ -67,7 +67,7 @@ export async function runCinematographer(
|
|||||||
),
|
),
|
||||||
},
|
},
|
||||||
],
|
],
|
||||||
{ temperature: 0.6, responseFormat: "json_object", tag: "cinematographer" },
|
{ temperature: 0.6, tag: "cinematographer" },
|
||||||
);
|
);
|
||||||
|
|
||||||
const parsed = parseJsonLoose<RawCinematographerOutput>(raw);
|
const parsed = parseJsonLoose<RawCinematographerOutput>(raw);
|
||||||
|
|||||||
@@ -423,7 +423,7 @@ export async function runWriterPlan(
|
|||||||
{ role: "system", content: WRITER_PLAN_SYSTEM },
|
{ role: "system", content: WRITER_PLAN_SYSTEM },
|
||||||
{ role: "user", content: buildWriterPlanUserMessage(session) },
|
{ role: "user", content: buildWriterPlanUserMessage(session) },
|
||||||
],
|
],
|
||||||
{ temperature: 0.9, responseFormat: "json_object", tag: "writer-plan" },
|
{ temperature: 0.9, tag: "writer-plan" },
|
||||||
);
|
);
|
||||||
|
|
||||||
const parsed = parseJsonLoose<RawPlan>(raw);
|
const parsed = parseJsonLoose<RawPlan>(raw);
|
||||||
@@ -473,7 +473,7 @@ export async function runWriterBeats(
|
|||||||
{ role: "system", content: WRITER_BEATS_SYSTEM },
|
{ role: "system", content: WRITER_BEATS_SYSTEM },
|
||||||
{ role: "user", content: buildWriterBeatsUserMessage(session, plan) },
|
{ role: "user", content: buildWriterBeatsUserMessage(session, plan) },
|
||||||
],
|
],
|
||||||
{ temperature: 0.9, responseFormat: "json_object", tag: "writer-beats" },
|
{ temperature: 0.9, tag: "writer-beats" },
|
||||||
);
|
);
|
||||||
|
|
||||||
const parsed = parseJsonLoose<RawBeats>(raw);
|
const parsed = parseJsonLoose<RawBeats>(raw);
|
||||||
|
|||||||
@@ -446,7 +446,7 @@ export async function directInsertBeat(
|
|||||||
content: buildInsertBeatUserMessage(session, freeformAction),
|
content: buildInsertBeatUserMessage(session, freeformAction),
|
||||||
},
|
},
|
||||||
],
|
],
|
||||||
{ temperature: 0.9, responseFormat: "json_object", tag: "insert-beat" },
|
{ temperature: 0.9, tag: "insert-beat" },
|
||||||
);
|
);
|
||||||
|
|
||||||
const parsed = parseJsonLoose<InsertBeatPartial>(raw);
|
const parsed = parseJsonLoose<InsertBeatPartial>(raw);
|
||||||
|
|||||||
Reference in New Issue
Block a user